
GATA [1]}: a powerful KG-based RL agent, which is the benchmark model for cooking games.

IL [2]}: a hierarchical agent which also uses two training phases. In the first phase, both the task selector and the action selector are pre-trained through imitation learning. Then in the second phase, the action selector is fine-tuned through reinforcement learning.

IL w/o FT: a variant of the IL baseline, where only the imitation pre-training phase is conducted, and there's no RL fine-tuning.

QWA: the proposed model with world-perceiving modules.

